Search Results for author:
Found 3 papers, 1 papers with code
S3LLM: Large-Scale Scientific Software Understanding with LLMs using Source, Metadata, and Document
S3LLM demonstrates the potential of using locally deployed open-source LLMs for the rapid understanding of large-scale scientific computing software, eliminating the need for extensive coding expertise, and thereby making the process more efficient and effective.
Rapid detection of rare events from in situ X-ray diffraction data using machine learning
These methods are often combined with external stimuli such as thermo-mechanical loading to take snapshots over time of the evolving microstructure and attributes.
Benchmarking and In-depth Performance Study of Large Language Models on Habana Gaudi Processors
Thirdly, we evaluate the performance of Transformers on GAUDI, particularly in handling long sequences and uncovering performance bottlenecks.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
